Abstract

State of the Union Addresses (SOUA) by two recent US Presidents, President Obama (2016) and President Trump (2018), and a series of recent of tweets by President Trump, are analysed by means of the data mining technique, sentiment analysis. The intention is to explore the contents and sentiments of the messages contained, the degree to which they di_er, and their potential implications for the national mood and state of the economy. President Trump's 2018 SOUA and his sample tweets are identi_ed as being more positive in sentiment than President Obama's 2016 SOUA. This is con_rmed by bootstrapped t tests and non-parametric sign tests on components of the respective sentiment scores. The issue of whether overly positive pronouncements amount to self-promotion, rather than intrinsic merit or sentiment, is a topic for future research.